About the Data

Data from Trial 49, in vivo assay performed from 20220203 - 20220214.

Timepoints

Treat with loperamide at 5 dpf for 24 hours.

Sample timepoint 1 at 6 dpf (24 hour treatment)
Sample timepoint 2 at 7 dpf (24 hour treatment + 24 hour water)
Sample timepoint 3 at 11 dpf (24 hour treatment + 5 days water)

Sampling on 2022.02.09, 02.10, 02.14.

Sample collection & plating

At each timepoint:

Wash all fish twice by transferring into sterile volvic in a 6-well plate
Add fish with 500 µL sterile volvic water into a fastprep tube
Homogenize sample at 6.5 for 45 seconds

For individual strains (1,2,3,4,10):
Make 0 to -3 dilutions in 96-well plates, in triplicate (8 fish per plate)
Plate 10 µL microdrops on big square plates.
8 square plates total per timepoint

For Bc1/Bc2/Bc3/Bc4/Bc10 condition:
Make 3 dilutions in 1.5 mL tubes: 100 µL into 900 µL water –> 10⁰, 10^-1, 10^-2, 10^-3
Spread 3 x 100 µL aliquots of each dilution on LB plates = 12 plates per fish
144 plates total per timepoint

Put plates at 28C for 2 days, then count colonies.

Conditions

Treatment (Strain)	Loperamide Treatment
	DMSO
	Loperamide 10 mg/L
Bc1
Bc1	DMSO
Bc1	Loperamide 10 mg/L
Bc2
Bc2	DMSO
Bc2	Loperamide 10 mg/L
Bc3
Bc3	DMSO
Bc3	Loperamide 10 mg/L
Bc4
Bc4	DMSO
Bc4	Loperamide 10 mg/L
Bc10
Bc10	DMSO
Bc10	Loperamide 10 mg/L
Bc1/Bc2/Bc3/Bc4/Bc10
Bc1/Bc2/Bc3/Bc4/Bc10	DMSO
Bc1/Bc2/Bc3/Bc4/Bc10	Loperamide 10 mg/L

Setup

Load libraries

Import data

# import individual strain data
datacfustrial49<-
   readxl::read_xlsx("Trial49_LoperamideZebrafishWaterCFUs.xlsx", sheet="Fish") %>%
   drop_na(DF) %>%
   mutate(LoperamideTreatment=factor(LoperamideTreatment, 
                                    levels=c("None", "DMSO", "Loperamide 10 mg/L"),
                                    labels=c("Control","DMSO", "Loperamide")),
         Treatment = factor(Treatment,
                            levels=c("Bc1","Bc2","Bc3","Bc4","Bc10","Bc1/Bc2/Bc3/Bc4/Bc10")),
         Timepoint = case_when(TrialDay == "6" ~ "24 hr treatment",
                                      TrialDay == "7" ~ "Treatment +\n24 hr recovery",
                                      TrialDay == "11" ~ "Treatment +\n5 day recovery"),
         Timepoint_day = case_when(TrialDay == "6" ~ "24hr",
                                      TrialDay == "7" ~ "48hr",
                                      TrialDay == "11" ~ "6d")) %>% 
   mutate(TimepointDay = factor(Timepoint_day, 
                          levels = c("24hr","48hr","6d"),
                          labels = c("T0","T1","T5")))

# import mix data
datacfusmixtrial49 <- 
   readxl::read_xlsx("Trial49_LoperamideZebrafishWaterCFUs.xlsx", sheet="FishMix") %>%
   drop_na(DF) %>%
   mutate(LoperamideTreatment=factor(LoperamideTreatment, 
                                     levels=c("None", "DMSO", "Loperamide 10 mg/L"),
                                     labels=c("Control","DMSO", "Loperamide")),
          Timepoint = case_when(TrialDay == "6" ~ "24 hr treatment",
                                      TrialDay == "7" ~ "Treatment +\n24 hr recovery",
                                      TrialDay == "11" ~ "Treatment +\n5 day recovery"),
         Timepoint_day = case_when(TrialDay == "6" ~ "24hr",
                                      TrialDay == "7" ~ "48hr",
                                      TrialDay == "11" ~ "6d")) %>% 
  group_by(Fish,Treatment,LoperamideTreatment,FishNum,TrialDay, Timepoint_day, Timepoint) %>% 
  summarise_all(.funs="mean", na.rm=TRUE) %>% 
   unite("LoperamideTimepoint", LoperamideTreatment,Timepoint_day, remove=FALSE) %>% 
   unite("FishID", LoperamideTreatment,Timepoint_day,FishNum, remove=FALSE) %>% 
   mutate(TimepointDay = factor(Timepoint_day, 
                          levels = c("24hr","48hr","6d"),
                          labels = c("T0","T1","T5")))


# import water data
watercfustrial49 <- 
   readxl::read_xlsx("Trial49_LoperamideZebrafishWaterCFUs.xlsx", sheet="Water") %>%
   filter(Treatment != "Bc1/Bc2/Bc3/Bc4/Bc10") %>%
   mutate(LoperamideTreatment=factor(LoperamideTreatment, 
                                    levels=c("None", "DMSO", "Loperamide 10 mg/L"),
                                    labels=c("Control","DMSO", "Loperamide")),
         Treatment = factor(Treatment, levels=c("Bc1","Bc2","Bc3","Bc4","Bc10")))

# import strain metadata


straininfo <- readxl::read_xlsx("../../LoperamideStrainInfo.xlsx") %>% 
   mutate(Strain=recode(Strain, "W6t"="W6"))

Fish CFUs per individual strain, all timepoints together

Stats of all significant comparisons

Treatment	Timepoint	Timepoint_day	.y.	group1	group2	p	p.adj	p.format	p.signif	method
Bc1	24 hr treatment	24hr	CFUs_perFish	DMSO	Loperamide	0.04206641	1	0.042	*	Wilcoxon
Bc2	24 hr treatment	24hr	CFUs_perFish	DMSO	Loperamide	0.02857143	1	0.029	*	Wilcoxon
Bc2	Treatment + 24 hr recovery	48hr	CFUs_perFish	DMSO	Loperamide	0.02857143	1	0.029	*	Wilcoxon
Bc1	Treatment + 5 day recovery	6d	CFUs_perFish	DMSO	Loperamide	0.02940105	1	0.029	*	Wilcoxon

First timepoint, total CFUs per Fish

Faceted by Strain, with means shown.

Stats are relative to DMSO

Timeline for each strain with mean

Timeline for each strain with boxplots

Mix community CFUs

Overall Mix CFUs per condition

Total mix CFUs per fish

Percent abundance of each strain per fish

CFUs of each strain per fish, log scale

CFUs by strain

Grouped by Timepoint

Grouped by Treament

## CFUs of Bc1 in mix

CFUs of Bc3 in mix

Mix Summary Figure

Alpha diversity

Beta diversity

All samples together

Just DMSO and loperamide

Each timepoint separately

Within group beta-diversity

## # A tibble: 36 × 8
##    .y.   group1       group2                  p   p.adj p.format p.signif method
##    <chr> <chr>        <chr>               <dbl>   <dbl> <chr>    <chr>    <chr> 
##  1 value Control_24hr Control_48hr    0.839     0.84    0.83945  ns       Wilco…
##  2 value Control_24hr Control_6d      0.742     0.79    0.74190  ns       Wilco…
##  3 value Control_24hr DMSO_24hr       0.0118    0.024   0.01180  *        Wilco…
##  4 value Control_24hr DMSO_48hr       0.00287   0.0074  0.00287  **       Wilco…
##  5 value Control_24hr DMSO_6d         0.0000933 0.00067 9.3e-05  ****     Wilco…
##  6 value Control_24hr Loperamide_24hr 0.664     0.79    0.66418  ns       Wilco…
##  7 value Control_24hr Loperamide_48hr 0.0000933 0.00067 9.3e-05  ****     Wilco…
##  8 value Control_24hr Loperamide_6d   0.000836  0.003   0.00084  ***      Wilco…
##  9 value Control_48hr Control_6d      0.279     0.36    0.27920  ns       Wilco…
## 10 value Control_48hr DMSO_24hr       0.0682    0.1     0.06824  ns       Wilco…
## # … with 26 more rows

## # A tibble: 1 × 6
##   .y.               p        p.adj p.format p.signif method        
##   <chr>         <dbl>        <dbl> <chr>    <chr>    <chr>         
## 1 value 0.00000000283 0.0000000028 2.8e-09  ****     Kruskal-Wallis

Water CFUs

Put Mono as a mix?

Sum of the mono-reconv does not equal the mix-reconv.
Also, increased colonization for each strain in mono-reconv than when part of a mix.

Trial 49 Loperamide CFUs

Rebecca Stevick/David Perez Pascual

updated 2022.02.23